I am currently working with a large customer and I am involved with servers located in two data centers, one with Solaris servers and the other one with Linux servers. The Solaris side is cleverly setup using zones and ZFS and this provides a very low virtualization overhead. I learned quite a lot about these [...]
MySQL 5.6 vs MySQL 5.5 and the Star Schema Benchmark
March 11, 2013 By 7 Comments
So far most of the benchmarks posted about MySQL 5.6 use the sysbench OLTP workload. I wanted to test a set of queries which, unlike sysbench, utilize joins. I also wanted an easily reproducible set of data which is more rich than the simple sysbench table. The Star Schema Benchmark (SSB) seems ideal for this. [...]
Percona Live MySQL Conference and Expo 2013: The talks I want to see
February 12, 2013 By 4 Comments
I’ve been woefully neglectful of my responsibilities to post regularly about Percona Live MySQL Conference and Expo 2013 (PLCME 2013), but here’s some highlights of what I am planning to attend from the schedule. Read to the very bottom for the chance to win a free full pass to the conference! When picking talks to attend, [...]
How does MySQL Replication really work?
January 9, 2013 By 9 Comments
While we do have many blog posts on replication on our blog, such as on replication being single-threaded, on semi-synchronous replication or on estimating replication capacity, I don’t think we have one that covers the very basics of how MySQL replication really works on the high level. Or it’s been so long ago I can’t [...]
Identifying the load with the help of pt-query-digest and Percona Server
December 29, 2011 By 3 Comments
Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make [...]
The case for getting rid of duplicate “sets”
May 17, 2011 By 2 Comments
The most useful feature of the relational database is that it allows us to easily process data in sets, which can be much faster than processing it serially. When the relational database was first implemented, write-ahead-logging and other technologies did not exist. This made it difficult to implement the database in a way that matched [...]
Distributed Set Processing with Shard-Query
May 14, 2011 By 27 Comments
Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: [...]
Shard-Query EC2 images available
May 11, 2011 By 2 Comments
Infobright and InnoDB AMI images are now available There are now demonstration AMI images for Shard-Query. Each image comes pre-loaded with the data used in the previous Shard-Query blog post. The data in the each image is split into 20 “shards”. This blog post will refer to an EC2 instances as a node from here [...]
Innodb Caching (part 2)
May 10, 2011 By 7 Comments
Few weeks ago I wrote about Innodb Caching with main idea you might need more cache when you think you are because Innodb caches data in pages, not rows, and so the whole page needs to be in memory even if you need only one row from it. I have created the simple benchmark which [...]
Innodb row size limitation
April 7, 2011 By 12 Comments
I recently worked on a customer case where at seemingly random times, inserts would fail with Innodb error 139. This is a rather simple problem, but due to it’s nature, it may only affect you after you already have a system running in production for a while.
